Results 11 to 20 of about 6,100,810 (194)
Reduced-Order modeling for Heston stochastic volatility model
In this paper, we compare the intrusive proper orthogonal decomposition (POD) with Galerkin projection and the data-driven dynamic mode decomposition (DMD), for Heston's option pricing model. The full order model is obtained by discontinuous Galerkin discretization in space and backward Euler in time.
Sinem Kozpınar +2 more
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Approximate deconvolution reduced order modeling [PDF]
This paper proposes a large eddy simulation reduced order model(LES-ROM) framework for the numerical simulation of realistic flows. In this LES-ROM framework, the proper orthogonal decomposition(POD) is used to define the ROM basis and a POD differential filter is used to define the large ROM structures.
Xie, X. +3 more
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Tandem Cascade Flow Prediction by POD-RBFN Reduced Order Model
The cost of obtaining a large amount of flow field information by traditional experiment or CFD is unacceptable,so it is of significance to develop faster forecasting calculation methods.Proper orthogonal decomposition(POD)is used to extract the dominant
SHANG Xun +3 more
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Control-Oriented, Data-Driven Models of Thermal Dynamics
We investigate data-driven, simple-to-implement residential environmental models that can serve as the basis for energy saving algorithms in both retrofits and new designs of residential buildings.
Ljuboslav Boskic, Igor Mezic
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Reduced-order modeling of hidden dynamics [PDF]
5 pages, 2 ...
Héas, Patrick, Herzet, Cédric
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AEROM: NASA’s Unsteady Aerodynamic and Aeroelastic Reduced-Order Modeling Software
The origins, development, implementation, and application of AEROM, NASA’s patented reduced-order modeling (ROM) software, are presented. Using the NASA FUN3D computational fluid dynamic (CFD) code, full and ROM aeroelastic solutions are computed at ...
Walter A. Silva
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Experimental Study of the Transient Behavior of a Wind Turbine Wake Following Yaw Actuation
Wind tunnel experiments were performed to investigate the response of a wind turbine model immersed in a replicated atmospheric boundary layer to dynamic changes in the yaw angle.
Derek Micheletto +2 more
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Full- and Reduced-order Model of Hydraulic Cylinder for Motion Control [PDF]
This paper describes the full- and reduced-order models of an actuated hydraulic cylinder suitable for system dynamics analysis and motion control design.
Ruderman, Michael
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IGBT Temperature Field Monitoring Based on Reduced-order Model
With the rapid development of the world economy, IGBT has been widely used in motor drive and electric energy conversion. In order to timely detect the fatigue damage of IGBT, it is necessary to monitor the junction temperature of IGBT.
Ziyu Zhou +5 more
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Uncertainty Analysis of Neutron Diffusion Eigenvalue Problem Based on Reduced-order Model
In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model ...
In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model based on POD-Galerkin method in core physical uncertainty analysis. The two-dimensional two group TWIGL benchmark question was taken as the research object, the key variation characteristics of the core flux distribution were extracted under the finite perturbation of the group constants of each material region, and the full-order neutron diffusion problem was projected on the variation characteristics to establish a reduced-order neutron diffusion model. The reduced-order model was used to replace the full-order model to carry out the uncertainty analysis of the group constants of the material region. The results show that the bias of the mathematical expectation of keff calculated by reduced-order and full-order models is close to 1 pcm. In addition, compared with the calculation time required for uncertainty analysis of full-order model, the analysis time of reduced-order model (including the calculation time of the full-order model required for the construction of reduced-order model) is only 11.48%, which greatly improves the efficiency of uncertainty analysis. The biases of mathematical expectation of keff calculated by reduced-order and full-order models based on Latin hypercube sampling and simple random sampling are less than 8 pcm, and under the same sample size, the bias from the Latin hypercube sampling result is smaller. From the TWIGL benchmark test results, under the same sample size, Latin hypercube sampling method is more recommended for POD-Galerkin reduced-order model.
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